Real-time monitoring across 30+ jurisdictions. Track every regulatory change, enforcement action, and emerging AI law worldwide.
30
Changes Tracked
30+
Jurisdictions Monitored
27
Frameworks Covered
ELDORET, Kenya, November 12th – The Office of the Data Protection Commissioner(ODPC) joined various stakeholders at the inaugural Kenya AI and Software Summit, hosted by the Ministry of Information, Communications, and Digital Economy. Under the theme “Software as a Catalyst for Inclusive Growth, Jobs, and Competitiveness,” Data Commissioner Immaculate Kassait delivered remarks during a high-level […]
<p>The National Privacy Commission (NPC), together with data protection authorities from across</p> <p>The post <a href="https://privacy.gov.ph/npc-joins-international-data-protection-authorities-in-statement-on-privacy-risks-of-ai-generated-imagery/">NPC Joins International Data Protection Authorities in Statement on Privacy Risks of AI-Generated Imagery</a> appeared first on <a href="https://privacy.gov.ph">National Privacy Commission</a>.</p>
New Jersey A4544 would regulate automated decision-making systems used by state agencies and large private entities. The bill requires impact assessments prior to deployment, ongoing auditing for discriminatory outcomes, public disclosure of system capabilities and limitations, and consumer access to human review of automated decisions. Covers employment, credit, insurance, and government benefit determinations.
Massachusetts SD 1372 would establish a comprehensive AI governance framework requiring organizations deploying high-risk AI systems to conduct algorithmic impact assessments, implement bias testing protocols, and maintain human oversight mechanisms. The bill targets AI used in employment screening, lending decisions, healthcare triage, and criminal justice risk assessment. It would create an AI Advisory Council to develop technical standards.
Virginia HB 2094 would impose duties on developers and deployers of high-risk AI systems operating in Virginia. Developers must provide model documentation, share bias testing results, and disclose known limitations to downstream deployers. Deployers must implement risk management programs, conduct impact assessments, and maintain records for audit purposes. The bill aligns closely with the NIST AI RMF governance framework and the Colorado AI Act.
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